在遗传性神经肌肉疾病中赋予临床医生人工智能。

Andi Nuredini, Marco Savarese, Filippo Maria Santorelli, Rossella Ginevra Tupler
{"title":"在遗传性神经肌肉疾病中赋予临床医生人工智能。","authors":"Andi Nuredini, Marco Savarese, Filippo Maria Santorelli, Rossella Ginevra Tupler","doi":"10.36185/2532-1900-927","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial Intelligence (AI) is the ability of machines to perform tasks that typically require human intelligence, such as learning, problem-solving, and decision-making. Its integration into healthcare may revolutionize many areas of medicine, including the diagnosis and management of neuromuscular disorders (NMDs).</p><p><p>These disorders, characterized by their clinical and genetical complexity and heterogeneity, demand innovative approaches to improve patient outcomes. Among these approaches, AI-driven solutions hold immense potential. However, the success of these solutions depends on preparing a new generation of clinicians equipped to harness the multifaceted power of AI.</p><p><p>One remarkable initiative addressing this need is the CoMPaSS-NMD project, which pioneers an interdisciplinary framework for developing AI-driven strategies to stratify patients using multiple clinical, histopathological, MRI e genetic datasets. By fostering a shared working language and integrating diverse competencies, the project aims to advance knowledge dissemination and bridge gaps between traditional disciplines. This approach is vital for addressing the challenges posed by NMDs, where early diagnosis and personalized treatment plans are critical.</p><p><p>To support this mission, the Young Investigator Training (YIT) initiative within CoMPaSS-NMD fosters education and scientific exchange among early-career researchers. By promoting high-quality clinical assessments and multidisciplinary training, YIT prepares a new generation to meet the evolving challenges in NMD care and research.</p>","PeriodicalId":93851,"journal":{"name":"Acta myologica : myopathies and cardiomyopathies : official journal of the Mediterranean Society of Myology","volume":"44 2","pages":"62-66"},"PeriodicalIF":0.0000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12250589/pdf/","citationCount":"0","resultStr":"{\"title\":\"Empowering clinicians with artificial intelligence in hereditary neuromuscular disorders.\",\"authors\":\"Andi Nuredini, Marco Savarese, Filippo Maria Santorelli, Rossella Ginevra Tupler\",\"doi\":\"10.36185/2532-1900-927\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Artificial Intelligence (AI) is the ability of machines to perform tasks that typically require human intelligence, such as learning, problem-solving, and decision-making. Its integration into healthcare may revolutionize many areas of medicine, including the diagnosis and management of neuromuscular disorders (NMDs).</p><p><p>These disorders, characterized by their clinical and genetical complexity and heterogeneity, demand innovative approaches to improve patient outcomes. Among these approaches, AI-driven solutions hold immense potential. However, the success of these solutions depends on preparing a new generation of clinicians equipped to harness the multifaceted power of AI.</p><p><p>One remarkable initiative addressing this need is the CoMPaSS-NMD project, which pioneers an interdisciplinary framework for developing AI-driven strategies to stratify patients using multiple clinical, histopathological, MRI e genetic datasets. By fostering a shared working language and integrating diverse competencies, the project aims to advance knowledge dissemination and bridge gaps between traditional disciplines. This approach is vital for addressing the challenges posed by NMDs, where early diagnosis and personalized treatment plans are critical.</p><p><p>To support this mission, the Young Investigator Training (YIT) initiative within CoMPaSS-NMD fosters education and scientific exchange among early-career researchers. By promoting high-quality clinical assessments and multidisciplinary training, YIT prepares a new generation to meet the evolving challenges in NMD care and research.</p>\",\"PeriodicalId\":93851,\"journal\":{\"name\":\"Acta myologica : myopathies and cardiomyopathies : official journal of the Mediterranean Society of Myology\",\"volume\":\"44 2\",\"pages\":\"62-66\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12250589/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Acta myologica : myopathies and cardiomyopathies : official journal of the Mediterranean Society of Myology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.36185/2532-1900-927\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta myologica : myopathies and cardiomyopathies : official journal of the Mediterranean Society of Myology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36185/2532-1900-927","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

人工智能(AI)是机器执行通常需要人类智能的任务的能力,例如学习、解决问题和决策。将其整合到医疗保健中可能会彻底改变许多医学领域,包括神经肌肉疾病(NMDs)的诊断和管理。这些疾病的特点是其临床和遗传的复杂性和异质性,需要创新的方法来改善患者的结果。在这些方法中,人工智能驱动的解决方案具有巨大的潜力。然而,这些解决方案的成功取决于培养新一代临床医生,使他们能够利用人工智能的多方面力量。解决这一需求的一个显著举措是CoMPaSS-NMD项目,该项目开创了一个跨学科框架,用于开发人工智能驱动的策略,利用多种临床、组织病理学、MRI和遗传数据集对患者进行分层。通过培养共同的工作语言和整合不同的能力,该项目旨在促进知识传播,弥合传统学科之间的差距。这种方法对于解决nmd带来的挑战至关重要,早期诊断和个性化治疗计划至关重要。为了支持这一使命,CoMPaSS-NMD的青年研究员培训(YIT)计划促进了早期职业研究人员的教育和科学交流。通过促进高质量的临床评估和多学科培训,YIT准备新一代,以应对NMD护理和研究中不断变化的挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Empowering clinicians with artificial intelligence in hereditary neuromuscular disorders.

Artificial Intelligence (AI) is the ability of machines to perform tasks that typically require human intelligence, such as learning, problem-solving, and decision-making. Its integration into healthcare may revolutionize many areas of medicine, including the diagnosis and management of neuromuscular disorders (NMDs).

These disorders, characterized by their clinical and genetical complexity and heterogeneity, demand innovative approaches to improve patient outcomes. Among these approaches, AI-driven solutions hold immense potential. However, the success of these solutions depends on preparing a new generation of clinicians equipped to harness the multifaceted power of AI.

One remarkable initiative addressing this need is the CoMPaSS-NMD project, which pioneers an interdisciplinary framework for developing AI-driven strategies to stratify patients using multiple clinical, histopathological, MRI e genetic datasets. By fostering a shared working language and integrating diverse competencies, the project aims to advance knowledge dissemination and bridge gaps between traditional disciplines. This approach is vital for addressing the challenges posed by NMDs, where early diagnosis and personalized treatment plans are critical.

To support this mission, the Young Investigator Training (YIT) initiative within CoMPaSS-NMD fosters education and scientific exchange among early-career researchers. By promoting high-quality clinical assessments and multidisciplinary training, YIT prepares a new generation to meet the evolving challenges in NMD care and research.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信